QRMine:扎根理论三角测量Python包

• 2020 年 4 月 3 日
• 筆記

扎根理论（GT）是在数据基础上建立理论的一种定性研究方式。GT采用文本和数值数据并进行意义构建数据的各个编码或标记阶段，例如：开放性编码和选择性编码。在编码过程中，机器学习（ML）技术，包括自然语言处理（NLP）都可以辅助研究人员。三角测量是将各种类型数据组合在一起的一个过程。ML有助于从数值数据中获得见解，进而证实文本采访记录中的调查结果。我们提供了一种开源python包（QRMine），它能够压缩各种ML和NLP库以支持GT中的编码和三角测量。QRMine能够使研究人员利用这些方法轻松地处理数据。研究人员可以安装python包索引（PyPI）中的QRMine并且能够辅助QRMine的开发工作。我们认为，计算的三角测量概念能够在大数据领域建立GT相关性。

原文题目：QRMine: A python package for triangulation in Grounded Theory

Grounded theory (GT) is a qualitative research method for building theory grounded in data. GT uses textual and numeric data and follows various stages of coding or tagging data for sense-making, such as open coding and selective coding. Machine Learning (ML) techniques, including natural language processing (NLP), can assist the researchers in the coding process. Triangulation is the process of combining various types of data. ML can facilitate deriving insights from numerical data for corroborating findings from the textual interview transcripts. We present an open-source python package (QRMine) that encapsulates various ML and NLP libraries to support coding and triangulation in GT. QRMine enables researchers to use these methods on their data with minimal effort. Researchers can install QRMine from the python package index (PyPI) and can contribute to its development. We believe that the concept of computational triangulation will make GT relevant in the realm of big data.

原文作者：Bell Raj Eapen, Norm Archer, Kamran Sartipi

原文地址：

https://arxiv.org/abs/2003.13519